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The purpose of this paper is to estimate the economic (namely cost, revenue and profit) efficiency and its association with intellectual capital of 37 BSE-listed Indian banks over the period 2005–2018.

This study employs truncated Tobit regression to compute the relationship between intellectual capital and estimated cost, revenue and profit efficiency using Data Envelopment Analysis (DEA) for the 37 BSE-listed Indian banks within the panel data framework.

Estimates suggest that banks’ overall annual average cost, revenue and profit efficiency are 0.4466–0.7519, 0.4825–0.8773 and 0.4905–0.8803, respectively, during the sample period. Further, Tobit regression results indicate that the aggregate intellectual capital (value-added intellectual coefficient or Modified Value-added Intellectual Capital) has a positive but minimal impact on these efficiency parameters at 1 percent significance level for the overall sample as well as public sector banks. Among all the sub-components of intellectual capital, human capital, structural capital and relational capital have a positive and moderate impact on these efficiency measures for the overall sample. Control variables, particularly bank size, are significant drivers of the estimated efficiency of banks.

Findings suggest that banks should invest adequately to enhance their overall intellectual capital to further augment these economic efficiency measures in the long run.

This study computes cost, revenue and profit efficiency of 37 BSE-listed banks based on DEA followed by intellectual capital using the Pulic approach (1998 and 2000) and the Bontis (1998) approach in the first stage. Later, it examines the dynamics between the computed efficiency parameters and intellectual capital using Tobit regression within the panel data framework.

This study empirically investigates the level of intellectual capital efficiency amongst the listed commercial banks in Nigeria and the factors influencing its efficient utilisation.

The paper employs the data envelopment analysis (DEA) to determine intellectual capital efficiency for the listed banks in Nigeria using data obtained from their annual financial reports from 2013 to 2019. After obtaining the efficiency scores, the Tobit regression technique was used to analyse the impact of firm-specific factors on intellectual capital efficiency.

The study found that only 8.33% of the sampled Nigerian commercial banks are at optimum capacity in utilising their intellectual capital, while 91.67% are inefficient. It also finds that bank size and directors' shareholdings positively impact intellectual capital efficiency, while market and ownership concentration debar the attainment of optimum intellectual capital efficiency.

This study contributes to very scare literature on intellectual capital efficiency measurements by using the non-parametric analysis (DEA) to measure intellectual capital efficiency for listed banks in Nigeria.

This study showcases the importance of measuring intellectual capital efficiency amongst listed banks in Nigeria. It provides more information to the regulators and stakeholders on the need to enforce the disclosure of the value created from intellectual capital investment.

This study contributes to the scarce literature on measuring intellectual capital efficiency using a non-parametric analysis (DEA). It also provides new insights into the factors that influence intellectual capital efficiency amongst listed commercial banks in Nigeria.

This paper investigates the impact of intellectual capital and its components on slack-based technical efficiency (SBM-TE) of banks.

Data envelopment analysis is used to compute SBM-TE scores and the Value-Added Intellectual Coefficient (VAIC™) model is used to measure intellectual capital. An unbalanced panel of 32 banks that operated from 2000 to 2017 has been used.

Overall, the efficiency scores are averaged at 79%, suggesting that an inefficient bank needs to enhance technical efficiency by 21% to be at par with the best performing banks. Beta-convergence and sigma-convergence exist among banks with faster speed evident among listed and local banks. Intellectual capital has a positive impact on SBM-TE and human capital is the main driver of technical efficiency among banks. This result is specifically evident among non-listed banks and foreign banks. Economies of scale property are also evident among the banks. Competition and asset tangibility inhibit technical efficiency among banks.

Banks are advised to invest in value-adding emerging technologies and their employees so as to enhance their efficiency. The study offers insights for policymakers, practitioners and researchers in emerging markets.

The study is premier in employing the SBM-TE to explain the intellectual capital and efficiency nexus, as well as, testing for both beta-convergence and sigma-convergence.

The purpose of this paper is to investigate the determinants of intellectual capital performance in the UK banks over the period 1999‐2005.

Multiple regression analysis is used to test the relationship between the intellectual capital performance as a dependent variable and certain independent variables.

Results indicate that the standard variables, bank profitability and bank risk, are important. The results also show that investment in information technology (IT) systems, bank efficiency, barriers to entry and efficiency of investment in intellectual capital variables, which have not been considered in previous studies, have a significant impact on intellectual capital performance.

More evidence is needed on the determinants of intellectual capital performance before any generalisation of the results can be made. In addition, the empirical tests were conducted only on the Major British Banks Group over the period 1999‐2005 and hence the results of the study cannot be assumed to extend beyond this group of banks or to different study periods.

The study might help the banking regulators in addressing the factors affecting intellectual capital performance to take actions towards developing their performance and in turn maximise their value creation.

This paper adds to the literature on the determinants of intellectual capital performance in banks. In particular, it tests the theories that investment in IT systems, bank efficiency, barriers to entry and efficiency of investment in intellectual capital have impact on intellectual capital performance.

The purpose of this study is to analyse the validity of the value added intellectual coefficient (VAIC) method as an indicator of intellectual capital.

The paper describes VAIC through its calculation formulae and aims to establish what exactly it is that the method measures. It also looks in detail at how intellectual capital is understood in the method, and discusses its conceptual confusions. Furthermore, the paper tests the hypothesis according to which VAIC correlates with a company's stock market value, and reflects the contradictory results of earlier studies.

The analyses show, first, that VAIC indicates the efficiency of the company's labour and capital investments, and has nothing to do with intellectual capital. Furthermore, the calculation method uses overlapping variables and has other serious validity problems. Second, the results do not lend support to the hypothesis that VAIC correlates with a company's stock market value. The main reasons behind the lack of consistency in earlier VAIC results lie in the confusion of capitalized and cash flow entities in the calculation of structural capital and in the misuse of intellectual capital concepts.

The analyses show that VAIC is an invalid measure of intellectual capital.

The result is important since the method has been widely used in micro and macro level analyses, but this is the first time it has been put to rigorous scientific analysis.

This study aims to investigate the intellectual capital–financial performance relationship using two models, namely the conventional Value-Added Intellectual Coefficient (VAIC) model and the adjusted Value-Added Intellectual Coefficient (A-VAIC) model.

This study is designed as a quantitative research focusing on the relationship between intellectual capital and financial performance of the banking industry in Indonesia. As many as 114 data are derived from the publicly listed banks on the Indonesia Stock Exchange for the period of 2012–2017. The multiple regression analysis is employed to test the hypotheses studied.

In general, the result confirms that intellectual capital affects financial performance. Although not all hypotheses of the study are supported by either the VAIC model or the A-VAIC model, the results provide a deeper and new insight on how each component of intellectual capital efficiency (human capital, structural capital, capital employed, innovation capital) relates to financial performance (return on asset, return on equity, asset turnover, price to book ratio). The results also justify that further improvements in measuring intellectual capital are still needed in the future.

This study limits its generalization since the sample is only in the Indonesian banking industry. Notwithstanding the limitation, the results imply that the Indonesian banking managers need to be aware of intellectual capital management because of its strategic role in enhancing financial performance.

This study contributes to the intellectual capital literature by providing empirical evidence on the use of both models, namely the conventional VAIC and the A-VAIC in the Indonesian banking industry research setting which is never been studied before.

This study has the social implication to the enhancement of the quality life of the society. The higher the quality of intellectual capital in the banking firms, the better the banks serve the needs of the community.

This study contributes to the IC literature by providing empirical research on the use of the VAIC model and the A-VAIC model in the Indonesian banking industry.

The purpose of this paper is to apply Value Added Intellectual Coefficient (VAIC™) of Pulic to compare quoted information technology and communication companies on the Istanbul Stock Exchange (ISE), in terms of intellectual capital efficiency. This study also examines VAIC™, and its components' impact on company performance.

Multiple regression analysis was employed to identify the variables that significantly contribute to the company performance. Data required to calculate VAIC™ and its components were obtained from the 2005‐2007 annual reports and balance sheets of the companies.

As a whole, all the companies had a relatively higher human capital efficiency than structural and capital efficiencies. In 2007, Turkcell was the most efficient company based on VAIC™ assessment, while Link Bilgisayar and Plastikkart were the least efficient companies. Additionally, the results of the study revealed that factors such as human capital efficiency, firm leverage, and firm size, predicted profitability well. Among them, human capital efficiency had the highest impact. In addition, capital employed efficiency was found to be a significant predictor of both productivity and return on equity, and the only determinant of market valuation was the firm size.

This study allowed ITC companies to benchmark themselves according to the intellectual capital efficiencies and develop strategies to enhance their company's performance.

This study is the first that measures intellectual capital performance and its impact on the company performance of the quoted information technology and communication companies on the ISE.

The purpose of this study is to empirically investigate the relationship between intellectual capital and corporate governance of Oman's financial sector companies. Intellectual capital has been found to successfully contribute to the economic wealth creation of firms in germane literature. Unfortunately, financial statements do not necessarily capture and reflect the contributions of intellectual capital, thereby leading to an information asymmetry between companies and users of financial statements. The research also investigates the relationship between corporate governance and intellectual capital efficiency across various financial subsectors.

Data are collected from annual reports available on Muscat Securities Market for 31 listed financial sector companies for the period 2012 to 2016 and analyzed using a multiple regression model. Intellectual capital is measured using Pulic's efficiency measure of value-added intellectual coefficient (VAIC). Corporate governance individual components such as board characteristics, audit committee characteristics and ownership structure are presented as independent variables.

The findings suggest that board size and frequency of audit committee meetings have a significant association with the intellectual capital efficiency of Oman's financial sector. VAIC and human capital efficiency of banks are also significantly influenced by most of the corporate governance mechanisms; however, other subsectors do not report such findings. Corporate governance of banks in comparison to other subsectors effectively engages in utilizing the potential of intellectual capital efficiency. Agency theory and resource dependency theory find limited support as a result of this study. The GMM results are not robust to the alternative instruments.

The sample size is small as the study is limited to the listed financial sector of Oman. Future studies can be extended to include all of Oman's or GCC’s listed companies. Additionally, the intellectual capital is measured using the construct of VAIC which suffers some limitations and can be overcome using other tools such as content analysis.

The findings of this study suggest that Oman's regulators can create an awareness strategy on highlighting the importance of intellectual capital for companies (board of directors and managers), investors, debtors and creditors. Further, Oman's Capital Market Authority and Muscat Securities Market need to strengthen the regulations related to intellectual capital.

This study extends intellectual capital and corporate governance literature by presenting the research outcome for Oman's financial sector. It is useful for Oman's financial sector companies to direct corporate governance measures for driving value creation of firms through the management of intellectual capital efficiency.

In developed countries, banks are perceived to accumulate a higher level of intellectual capital than firms in other sectors. However, this perception has not been considered or tested in the context of an emerging market such as Vietnam, which has one of the most dynamic economies in the Asian region. This study estimates and compares the level of accumulation of intellectual capital and its four components by financial and nonfinancial firms in Vietnam. Furthermore, this study examines the relationship between intellectual capital and its components and the performance of financial and nonfinancial firms.

This study uses data collected from the annual reports of 75 financial and 75 nonfinancial firms in Vietnam from 2011 to 2018. A modified value-added intellectual coefficient model is adopted to measure the level of intellectual capital at firms. Various aspects of intellectual capital are considered, including the efficiency of human capital, structural capital, capital employed and relational capital. In addition, the generalized method of moments is used to ensure the robustness of the findings.

Findings in this study indicate that financial firms in Vietnam have accumulated a higher level of intellectual capital than nonfinancial firms. In addition, intellectual capital contributes positively to financial firms' performance. Three components of intellectual capital – structural capital efficiency, capital employed efficiency and relational capital efficiency – positively affect performance by financial firms.

This study is limited to financial and nonfinancial firms in Vietnam. Empirical studies in the future should incorporate the efficiency aspects of these types of firms because different industries might have different characteristics, in particular, their current efficiency level, which might cause differences in relation to the accumulation of intellectual capital.

The findings of this study provide valuable evidence and implications for executives and policymakers in creating, managing and enhancing intellectual capital within the Vietnamese context, in particular in the financial sector.

To the best of our knowledge, this is the first empirical study conducted in the context of Vietnam, with the following two objectives: (1) to measure and compare the level of accumulation of intellectual capital by financial and nonfinancial firms in Vietnam; and (2) to examine the contribution of intellectual capital and its components to the performance by financial and nonfinancial firms in Vietnam.

The purpose of this paper is to examine the effect of intellectual capital on bank productivity in an emerging market in Africa.

The Malmquist productivity index (MPI) is employed to estimate productivity growth of 18 banks in Ghana from 2003 to 2011 while the Value Added Intellectual Coefficient (VAIC) is used to measure bank intellectual capital performance. The panel-corrected standard errors estimation technique is used to estimate a panel regression model with MPI as the dependent variable. Bank market concentration and bank size are controlled for in the regression analysis.

The authors find productivity growth to be largely driven by efficiency changes compared to technological changes. The results from the regression analysis indicate that VAIC has a positive effect on the productivity of banks in Ghana. The authors also find human capital efficiency and capital employed efficiency as the components of VAIC that drive productivity growth in the banking industry. Bank size and industry concentration are also identified as significant drivers of productivity in the market.

The study’s findings support investments in intellectual capital as a means of improving the performance of banks in emerging markets.

To the best of the knowledge, this is the first study to empirically examine the relationship between intellectual capital and productivity in an emerging banking market in Africa.